To help you understand your New Relic usage and billing, we provide a usage UI for understanding your billing-related usage. Additionally, you can run custom NRQL queries to get additional detail, and you can create alert notifications for when your usage has reached certain levels.
The usage UI displays your data ingest over time. If you need more detail than the UI provides, you can use NRQL queries like these:
For information about data ingest limits and query limits, see New Relic data limits.
For a display of your user count, see the usage UI. If you need more detail than that, you can use the example NRQL queries below. For details about how users are calculated, see Billable user calculations.
Most New Relic organization have the ability to add core users. This section includes queries that will work for those organizations. If you're in an older organization that hasn't opted in to unlock core users, see Queries for organizations without core users.
Here are some rules for querying your users:
- Use only the
- The attributes used for querying users are
Here are some example NRQL queries for determining user count:
This query shows the billable full platform users for the month. In other words, it shows how much you'd be billed for your full platform users for that month if you were billed right now.
FROM NrMTDConsumptionSELECT latest(FullPlatformUsersBillable)
This query shows the number of core users you'd be billed for if you were billed right now:
FROM NrMTDConsumptionSELECT latest(CoreUsersBillable)
Here's a query for getting the current month's cost for your full platform users. Note that you'll have to know your organization's full platform user cost.
FROM NrMTDConsumption SELECT latest(FullPlatformUsersBillable) * YOUR_PER_FULL_PLATFORM_USER_COST
These queries apply for some older New Relic organizations that have only two user types available: basic users and full platform users.
There are a certain number of synthetics checks included for free with each edition. For details on that, see Synthetics limits.
The NrDailyUsage event is the event type that can best help you understand synthetics usage. It's generated once per day. Usage timestamps correspond to the time that New Relic receives and processes a synthetic check. This may introduce a slight difference in usage data compared to the time the synthetic check was executed.
FACET, you can break your consumption into multiple categories, including account, location, monitor type, and monitor name. If you have a parent account structure, ensure you run queries in a parent account to see the aggregated usage for that parent and its child accounts.
Both successful and failed checks contribute to overall synthetics consumption. Below are sample queries to view and facet your synthetics consumption:
Here are some query recommendations for helping you understand the estimated cost for the current month.
To help manage your billing, you can set alerts to notify you of unexpected increases in data ingest or user count.
Before building usage-related alert conditions, here are some tips:
- For basics about how to set up alerts, see NRQL alert conditions.
- The event timer aggregation method is recommended because it works best for infrequent data.
Here are some NRQL alert condition examples.
For setting up alerts related to data ingest limits and query limits, see Set alerts for hitting data limits.
To see changes made to your account (for example, changes related to managing users), you can query
For an advanced deep dive into managing data ingest in a complex organization, see Data ingest governance.
These are the primary events to query for understanding your usage:
NrConsumptionrecords usage every hour, and is the equivalent of "real-time" usage. Use this event to observe usage trends over time.
NrMTDConsumptiongenerates aggregate values from the
NrConsumptionevent. Use this event to see usage by monthly billing period. This is the best event for querying user count.
Here are some of the most important attributes attached to usage-related events.
The category of usage. There are three options:
This consolidates multiple categories of usage into a single metric. Helpful when faceting by
ID of the New Relic account directly responsible for the stored events, as determined from the used.
One tool you can use to learn more about your usage is the function
bytecountestimate() (for example, see this query that uses it).
Some important points to know about using
- Because it returns all data it finds, and some of that data doesn't count towards your ingest and billing, it's only an estimate of your actual usage. For that reason, it's mostly useful for researching the data reported by various sources, or for understanding the upper ceiling of data reported.
- We recommend using it mainly for querying time ranges under 24 hours, and, if desired, using that to extrapolate. This is because it's a function that requires querying a lot of data, and because it won't find data that passes retention boundaries.
For more about estimating usage, see our blog post about estimating usage.
Here are some technical details about how
- There are several types of data that don't count towards ingest but that is returned by the
bytecountestimate()function. This means that this function sometimes shows more data than actually is counted towards your usage. It may rarely show a lower amount but, if it does, it will be only slightly lower.
- Some telemetry data reported from an entity shares common attributes (for example, attributes about your New Relic account). We don't count the duplicated attributes towards your ingest, but
bytecountestimate()does count those attributes. This can sometimes result in a large discrepency between a
bytecountestimate()query and your actual usage.
- Our APM, browser monitoring, and mobile monitoring report a type of data known as metric timeslice data. This data isn't stored in NRDB like our other data types are, and so trying to use
bytecountestimate()on this data can result in confusing results. When querying this data, we recommend faceting by application name, and not by the metric name.